Xiaoyang Guo

Xiaoyang Guo (郭晓阳)

I am currently a Principal Researcher at Horizon Robotics, where I lead a team dedicated to 3D reconstruction, generation, and simulation for autonomous driving systems. I received my Ph.D. from the Multimedia Laboratory (MMLab) at The Chinese University of Hong Kong, where I was fortunate to be advised by Prof. Xiaogang Wang and Prof. Hongsheng Li. Prior to that, I obtained my Bachelor's degree in Computer Science from Tsinghua University.

My research interests lie at the intersection of 3D computer vision and generative AI, with a particular focus on large-scale 3D reconstruction, neural rendering, and scene generation.

I am actively seeking highly motivated interns to collaborate on projects involving neural rendering, video generation, and 3D foundation models. If you're interested, feel free to reach out via email.

Email / CV / Scholar / Github

	Rad: Training an End-to-end Driving Policy via Large-scale 3dgs-based Reinforcement Learning Hao Gao, Shaoyu Chen, Bo Jiang, Bencheng Liao, Yiang Shi, Xiaoyang Guo, Yuechuan Pu, Haoran Yin, Xiangyu Li, Xinbang Zhang, Ying Zhang, Wenyu Liu, Qian Zhang, Xinggang Wang Preprint, Arxiv'25 [arXiv] [project page]
	SynthDrive: Scalable Real2Sim2Real Sensor Simulation Pipeline for High-Fidelity Asset Generation and Driving Data Synthesis ZhengQing Chen, Ruohong Mei, Xiaoyang Guo^†, Qingjie Wang, Yubin Hu, Wei Yin, Weiqiang Ren, Qian Zhang International Conference on Intelligent Robots and Systems, IROS'25 [arXiv] [project page] [paper] [video]
	Boost 3D Reconstruction using Diffusion-based Monocular Camera Calibration Junyuan Deng, Wei Yin, Xiaoyang Guo^‡, Qian Zhang, Xiaotao Hu, Weiqiang Ren, Xiao-Xiao Long, Ping Tan^† International Conference on Computer Vision, ICCV'25 [arXiv] [code]
	Epona: Autoregressive Diffusion World Model for Autonomous Driving Kaiwen Zhang, Zhenyu Tang, Xiaotao Hu, Xingang Pan, Xiaoyang Guo, Yuan Liu, Jingwei Huang, Li Yuan, Qian Zhang, Xiaoxiao Long, Xun Cao, Wei Yin International Conference on Computer Vision, ICCV'25 [arXiv] [project page] [code]
	StableDepth: Scene-Consistent and Scale-Invariant Monocular Depth Zheng Zhang, Lihe Yang, Tianyu Yang, Chaohui Yu, Xiaoyang Guo, Yixing Lao, Hengshuang Zhao International Conference on Computer Vision, ICCV'25 (Spotlight) [arXiv]
	NGP-RT: Fusing Multi-Level Hash Features with Lightweight Attention for Real-Time Novel View Synthesis Yubin Hu, Xiaoyang Guo, Yang Xiao, Jingwei Huang, Yong-Jin Liu European Conference on Computer Vision, ECCV'24 (Realtime streamed on Petal Map App) [arXiv] [paper]
	SS3DM: Self-Supervised 3D Reconstruction from Monocular Videos Yubin Hu, Kairui Wen, Heng Zhou, Xiaoyang Guo, Yong-Jin Liu Advances in Neural Information Processing Systems, NeurIPS'24 (DB Track) [arXiv] [project page] [dataset]
	ArrangementNet: Learning Scene Arrangements for Vectorized Indoor Scene Modeling Jingwei Huang, Shanshan Zhang, Bo Duan, Xiaoyang Guo, Minwei Sun, Li Yi ACM Transactions on Graphics (TOG) , TOG'23 (Journal Track) [arXiv] [paper]
	LIGA-Stereo: Learning Lidar Geometry aware Representations for Stereo-based 3d Detector Xiaoyang Guo, Shaoshuai Shi, Xiaogang Wang, Hongsheng Li International Conference on Computer Vision), ICCV'21 (Ranked 1st place among stereo-based 3D detection methods on KITTI (July 2021), refer to here.) [arXiv] [project page] [paper] [code]
	Group-wise Correlation Stereo Network Xiaoyang Guo, Kai Yang, Wukui Yang, Xiaogang Wang, Hongsheng Li Conference on Computer Vision and Pattern Recognition, CVPR'19 [arXiv] [paper] [code]
	Unsupervised Cross-Spectral Stereo Matching by Learning to Synthesize Xiaoyang Guo, Mingyang Liang, Hongsheng Li, Xiaogang Wang, You Song AAAI, AAAI'19 (Oral Presentation) [arXiv] [paper]
	Learning Monocular Depth by Distilling Cross-domain Stereo Networks Xiaoyang Guo, Hongsheng Li, Shuai Yi, Jimmy Ren, Xiaogang Wang European Conference on Computer Vision, ECCV'18 [arXiv] [paper] [video] [code]
	Neural Network Encapsulation Hongyang Li, Xiaoyang Guo, Bo Dai, Wanli Ouyang, Xiaogang Wang European Conference on Computer Vision, ECCV'18 [arXiv] [paper]

Thanks for the template from Jon Barron .